## # A tibble: 81 × 3
## site freq pop
## <chr> <dbl> <dbl>
## 1 Rib Lake WWTF 1.4 386
## 2 Neopit WWTF 1 1000
## 3 Wolf River Ranch WWTF 1 1000
## 4 Red Cliff WWTP 1.2 1900
## 5 Spencer WWTP 1.3 2000
## 6 Washburn WWTP 1 2200
## 7 Hayward WPCF 1.3 2375
## 8 Keshena WWTF 1 2500
## 9 Spooner WWTP 1 2700
## 10 Mondovi WWTF 1 2800
## # … with 71 more rows
##
## Call:
## lm(formula = missed_percent ~ MSE + window + quant + FlagType,
## data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5954 -0.3097 0.0634 0.3445 1.4235
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.637168 1.799693 0.910 0.36921
## MSE 0.171105 0.051553 3.319 0.00212 **
## window -0.014304 0.007813 -1.831 0.07567 .
## quant -1.753772 1.038178 -1.689 0.10006
## FlagTypeflag.ntile.Pval 0.213933 0.217533 0.983 0.33213
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6075 on 35 degrees of freedom
## Multiple R-squared: 0.8401, Adjusted R-squared: 0.8218
## F-statistic: 45.96 on 4 and 35 DF, p-value: 1.84e-13
## # A tibble: 1 × 1
## `mean(abs(flag_error) > edgeThresh, na.rm = TRUE)`
## <dbl>
## 1 0.0310
## # A tibble: 1 × 1
## `mean(missed_percent == 0)`
## <dbl>
## 1 0.167
## # A tibble: 1 × 1
## `mean(missed_percent == 0)`
## <dbl>
## 1 0.309
##
## Call:
## lm(formula = missed_percent ~ FlagType + window + quant + sample_rate +
## pop + MSE, data = ., weights = num_flags)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -79.738 -14.756 2.896 23.931 122.590
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.507319 0.732706 -6.152 1.05e-09 ***
## FlagTypeflag.ntile 0.199273 0.251935 0.791 0.429
## FlagTypeflag.ntile.Pval 0.448996 0.317234 1.415 0.157
## window 0.001122 0.003593 0.312 0.755
## quant 0.112472 0.765338 0.147 0.883
## sample_rate 0.093204 0.066562 1.400 0.162
## pop 0.886151 0.137856 6.428 1.87e-10 ***
## MSE 0.237068 0.005806 40.830 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 34.24 on 1189 degrees of freedom
## (19 observations deleted due to missingness)
## Multiple R-squared: 0.6764, Adjusted R-squared: 0.6745
## F-statistic: 355 on 7 and 1189 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = missed_percent ~ FlagType + window + quant + sample_rate +
## pop + MSE, data = ., weights = 1/(Var + 1))
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -3.5088 -0.3359 -0.0048 0.3408 2.7035
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.4751744 0.4199523 -1.131 0.258
## FlagTypeflag.ntile -0.1292648 0.1533261 -0.843 0.399
## FlagTypeflag.ntile.Pval 0.0106984 0.1482819 0.072 0.942
## window -0.0007534 0.0018470 -0.408 0.683
## quant 0.0222290 0.3879586 0.057 0.954
## sample_rate 0.0075672 0.0333262 0.227 0.820
## pop 0.1386288 0.0777969 1.782 0.075 .
## MSE 0.1468614 0.0049289 29.796 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6941 on 1165 degrees of freedom
## (43 observations deleted due to missingness)
## Multiple R-squared: 0.4647, Adjusted R-squared: 0.4615
## F-statistic: 144.5 on 7 and 1165 DF, p-value: < 2.2e-16
